Xiangning Chen

Publications (76) View all

• Article: A Rapid Association Test Procedure Robust under Different Genetic Models Accounting for Population Stratification.

  Wenan Chen, Xiangning Chen, Kellie J Archer, Nianjun Liu, Qizhai Li, Zhongming Zhao, Shumei Sun, Guimin Gao
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  ABSTRACT: Objective: For genome-wide association studies (GWAS) using case-control data with stratification, a commonly used association test is the generalized Armitage (GA) trend test implemented in the software EIGENSTRAT. The GA trend test uses principal component analysis to correct for population stratification. It usually assumes an additive disease model and can have high power when the underlying disease model is additive or multiplicative, but may have relatively low power when the underlying disease model is recessive or dominant. The purpose of this paper is to provide a test procedure for GWAS with increased power over the GA trend test under the recessive and dominant models, while maintaining the power of the GA trend test under the additive and multiplicative models. Methods: We extend a Hardy-Weinberg disequilibrium (HWD) trend test for a homogeneous population to account for population stratification, and then propose a robust association test procedure for GWAS that incorporates information from the extended HWD trend test into the GA trend test. Results and Conclusions: Our simulation studies and application of our method to a GWAS data set indicate that our proposed method can achieve the purpose described above.
  Human Heredity 04/2013; 75(1):23-33. · 1.79 Impact Factor
• Article: Response to Commentary by Pedersen et al.

  Jianguang Ji, Kristina Sundquist, Yi Ning, Kenneth K Kendler, Jan Sundquist, Xiangning Chen
  Schizophrenia Bulletin 03/2013; · 8.80 Impact Factor
• Article: Canonical correlation analysis for RNA-seq co-expression networks.

  Shengjun Hong, Xiangning Chen, Li Jin, Momiao Xiong
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  ABSTRACT: Digital transcriptome analysis by next-generation sequencing discovers substantial mRNA variants. Variation in gene expression underlies many biological processes and holds a key to unravelling mechanism of common diseases. However, the current methods for construction of co-expression networks using overall gene expression are originally designed for microarray expression data, and they overlook a large number of variations in gene expressions. To use information on exon, genomic positional level and allele-specific expressions, we develop novel component-based methods, single and bivariate canonical correlation analysis, for construction of co-expression networks with RNA-seq data. To evaluate the performance of our methods for co-expression network inference with RNA-seq data, they are applied to lung squamous cell cancer expression data from TCGA database and our bipolar disorder and schizophrenia RNA-seq study. The preliminary results demonstrate that the co-expression networks constructed by canonical correlation analysis and RNA-seq data provide rich genetic and molecular information to gain insight into biological processes and disease mechanism. Our new methods substantially outperform the current statistical methods for co-expression network construction with microarray expression data or RNA-seq data based on overall gene expression levels.
  Nucleic Acids Research 03/2013; · 8.03 Impact Factor
• Article: Genetic association between RGS1 and internalizing disorders.

  John M Hettema, Seon-Sook An, Edwin J C G van den Oord, Michael C Neale, Kenneth S Kendler, Xiangning Chen
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  ABSTRACT: OBJECTIVE: Quantitative trait loci identified in animal models provide potential candidate susceptibility loci for human disorders. In this study, we investigated whether internalizing disorders (anxiety disorders, major depression, and neuroticism) were associated with a region on human chromosome 1 syntenic with a quantitative trait locus for rodent emotionality. METHODS: We genotyped 31 single-nucleotide polymorphisms in genes located on chromosome 1q31.2 in a two-stage association study of 1128 individuals chosen for a high or a low genetic risk for internalizing disorders from the Virginia Adult Twin Study of Psychiatric and Substance Use Disorders. RESULTS: None of the individual single-nucleotide polymorphisms showed consistent association across stages. A four-marker haplotype in the regulator of G-protein signaling 1 gene (RGS1) was significantly associated with decreased internalizing risk in both stages, whereas another showed a nominal association with a higher risk. CONCLUSION: Our data suggest that markers in the RGS1 gene might be in linkage disequilibrium with a protective allele that reduces the risk of anxiety and depressive disorders.
  Psychiatric genetics 01/2013; · 2.33 Impact Factor
• Article: Genetic association study between RGS2 and anxiety-related phenotypes.

  John M Hettema, Cuie Sun, Xiangning Chen, Kenneth S Kendler
  Psychiatric genetics 12/2012; · 2.33 Impact Factor